Mixed Integer Programming Applied to Radiation Treatment Planning Optimization

eva K. LeeGA Tech Res Corp - git混合整数规划（MIP）领域涉及理论分析、算法和软件开发以及科学计算的迷人而生动的混合。在过去的三十年中，实际应用为推进这一不断发展的学科的前沿提供了宝贵的见解和动力。特别是，MIP建模范例和相关的算法分支绑定、分支切断和分支价格解决方案策略已经非常成功地应用于广泛的工业应用，从调度和工艺规划应用到VLSI和电信网络设计。这些MIP的成功应用离不开优化研究人员和每个应用领域的领域专家之间的密切合作。在每种情况下，许多研究都致力于为手头的特定应用开发一个高级模型（而不仅仅是一个正确的公式，因为解决过程在很大程度上取决于公式模型的底层结构）和有效的计算策略。除了这些积极的研究之外，还出现了将计算进步的技术转移到商业软件（例如，CPLEX， XPRESS）中，使这些进步能够集成到从业者每天使用的决策支持系统中。本研究的主要重点是探索混合整数规划策略在放射治疗治疗计划优化中的应用。最初的重点将是放射外科治疗计划。放射外科包括对大脑进行小范围、立体定向的外部光束照射。在过去的十年中，它已经发展成为治疗和控制某些中枢神经系统病变如动静脉畸形、转移性病变、听神经瘤、垂体瘤、恶性胶质瘤和其他颅内肿瘤的常用方法。尽管放射外科手术为有效治疗这些疾病提供了极好的潜力，但大脑结构内部和之间的复杂性和功能依赖性意味着该手术本质上是高风险的，并可能带来严重的并发症。因此，在立体定向放射手术的计划和实施中，准确性和精确性是至关重要的。

Proposal #0098219Eva K. LeeGA Tech Res Corp -GITThe field of mixed integer programming (MIP) involves a fascinating and lively blend of theoretical analysis, algorithm and software development, and scientific computing. Over the past thirty years, real applications have provided invaluable insight and motivation for advancing the frontiers of this evolving discipline. In particular, the MIP modeling paradigm and the associated algorithmic branch-and-bound, branch-and-cut, and branch-and-price solution strategies have been applied extremely successfully to a broad range of industrial applications, from scheduling and process planning applications, to VLSI and telecommunication network design. Integral to these successful applications of MIP were close collaborations between optimization researchers and the domain experts in each application area. In each case, much research was devoted to developing a superior model (versus simply a correct formulation, as the solution process depends heavily on the underlying structure of the formulated model) and effective computational strategies for the specific application at hand. Beyond this active research came the technological transfer of computational advances into commercial software (e.g., CPLEX, XPRESS), enabling the integration of these advances into the decision support systems used daily by practitioners.The primary focus of this research is to explore applications of mixed integer programming strategies to radio-therapy treatment planning optimization. The initial focus will be radiosurgery treatment planning. Radiosurgery involves small field, stereotactic external beam irradiation to the brain. It has evolved over the past decade into a common method for treating and controlling certain central nervous system lesions such as arteriovenous malformations, metastatic lesions, acoustic neuromas, pituitary tumors, malignant gliomas and other intracranial tumors. Although radiosurgery provides an excellent potential for effectively curing these disorders, the complexities and functional dependencies both within and between brain structures means that the procedure is inherently high-risk and can bring about severe complications. Hence, accuracy and precision are of paramount importance in both the planning and execution of stereotactic radiosurgery.